1. Field of the Invention
This invention relates to data detection, and more particularly, to data detection apparatus which reproduces and detects data subjected to digital recording, for example, on a magnetic recording medium.
2. Description of the Related Art
Data subjected to digital recording on a recording medium, such as a magnetic tape, a magnetic disk or the like, are reproduced (demodulated), for example, by (1) binary-value determination for each bit by integral detection, (2) three-value determination using differential equalization, partial-response (1, 0, -1) equalization, partial-response (1, 1) equalization, or the like, (3) combination of Viterbi decoding, which is a kind of maximum likelihood decoding, and three-value determination.
Since integral equalization is a kind of two-value determination, it is stable against variations in the level of the reproduced output and has a large margin in timing at a detection point. A low-frequency-emphasizing-type waveform equalizer used for integral equalization, partial-response (1, 1) equalization or the like has low high-frequency noise. Low-frequency compensation is unnecessary for differential equalization and partial-response (1, 0, -1) equalization.
Viterbi decoding is a decoding method which efficiently executes maximum likelihood decoding utilizing a repetitive structure of correlative codes, such as convolution codes, partial-response equalization or the like. Viterbi decoding is known to have a low error rate in a decoding operation, and has attracted notice as a means to realize high-density data recording. It has been known that by being combined with a three-value-determination equalization method, such as differential equalization or the like, Viterbi decoding can perform a decoding operation with a lower error rate than a decoding operation for each bit. (Refer, for example, to "The Viterbi Algorithm", Proceeding of IEEE, Vol. 61, No. 3, March, 1973).
Low-frequency-emphasizing-type waveform equalization methods, such as integral equalization, partial-response (1,1) and the like, have the advantage of a relatively large margin in detection timing. However, such a method generally requires low-frequency cut-off, since low-frequency components are emphasized in the noise spectrum in the output of an equalizer. If low-frequency components are cut off at a high frequency, while the S/N ratio is improved, an equalization error caused by low-frequency cut-off distortion increases, and the I-pattern numerical aperture is reduced.
FIG. 1 illustrates a noise-spectrum distribution 100 for integral equalization. FIG. 2 illustrates a recorded waveform 110 and the corresponding integral-equalized waveform 120. In FIGS. 1 and 2, solid lines represent a case in which low-frequency components are not cut off, and broken lines represent a case in which low-frequency components are cut off. As can be understood from FIG. 2, an equalization error .DELTA.a is produced when low-frequency components are cut off, since low-frequency components are attenuated. In addition, as can be understood from FIG. 1, when low-frequency components are not cut off, the noise level increases as the frequency is reduced and finally diverges. On the other hand, when low-frequency components are cut off, the S/N ratio is improved since the low-frequency noise is cut off.
Since integral equalization is a kind of binary determination, Viterbi decoding cannot be applied to integral equalization in an unmodified state.
Equalization methods which do not require low-frequency compensation, such as differential equalization, partial response (1, 0, 1) equalization and the like, have a small margin in timing at a detection point, and have greater high-frequency noise than low-frequency-emphasizing-type equalization.